Systematic reviews and meta-analyses in the cerebrovascular space: essential domains for readers

Systematic Review and Meta-Analysis (SRMAs) in neurosurgery have significantly increased. With approximately 1 million patients affected by cerebrovascular disease annually, interpreting SRMAs necessitates a systematic approach. The objective of this review is to identify and describe four essential domains for SRMA interpretation.

This review outlines the necessities of reviewing existing literature and methodological frameworks essential for interpreting cerebrovascular neurosurgery SRMAs. Each domain is to accurately assess study design variations, heterogeneity assessment methods, outcome comparability strategies, and the impact of technological advancements and time bias on study outcomes.

Study design evaluation distinguishes between randomized controlled trials (RCTs) and non-randomized studies. RCTs provide high internal validity, but as seen in the ARUBA trial, can contain internal flaws that necessitate a deeper understanding before application to clinical practices. Non-randomized studies offer valuable real-world insights. A heterogeneity assessment involves readers and writers accurately using forest plots, Cochrane's Q test, Higgins I² statistics, subgroup analysis, and meta-regressions to understand a study's clinical findings. The expertise thresholds, as in the NASCET trial, significantly impact a study's external validity. Strategies such as the GRADE approach can assist in managing diverse outcome measures. Technological advancements, particularly in endovascular procedures and SRS, influence the accuracy of comparing studies across periods, and thus swiftly outdate older studies, lowering the applicability of SRMAs.

Effective interpretation of cerebrovascular neurosurgery SRMAs requires attention to study design, heterogeneity, outcome comparability, and technological advancements. These domains collectively enable evidence-based clinical decision-making and optimized patient care in a dynamic field.